Systems and methods for providing personalized transaction recommendations

Abstract

The present disclosure relates to systems and methods for recommending transaction amounts including: receiving a request for a transaction recommendation associated with a customer; receiving a plurality of traits associated with the customer; identifying a characteristic associated with one or more groups of customers based on the plurality of traits; automatically generating a transaction model associated with the identified characteristic associated with the one or more groups of customers; ranking the potential transactions; and generating at least one transaction recommendation for the customer based on the transaction model.

1 . A system for recommending transactions to customers based on customer characteristics, comprising:
 at least one machine-readable memory storing computer-executable instructions; and   at least one processor configured to execute the instructions to perform operations comprising:
 receiving a request for a transaction recommendation associated with a specified customer; 
 receiving a plurality of traits associated with the specified customer
 wherein receiving the plurality of traits comprises:
 accessing, via an application programming interface, social network data associated with the customer, 
 identifying, based on the social network data, one or more elements in content accessed by the customer; and 
 determining one or more interests of the user based on the one or more elements, wherein the one or more interests are associated with the plurality of traits; 
 
 
 identifying a characteristic associated with a customer group, based on the traits; 
 generating, by a machine learning process trained on customer data, a transaction model associated with the identified characteristic, the transaction model identifying potential transaction information associated with an entity by the customer group; 
 determining a plurality of potential transactions using the transaction model, each potential transaction being associated with a likelihood of the customer completing the potential transaction; 
 ranking the potential transactions using the transaction model; and 
 generating a transaction recommendation for the specified customer based on the transaction model, the transaction recommendation comprising a transaction amount and a transaction recipient to receive the transaction amount from the customer. 
   
     
     
         2 . The system of  claim 1 , wherein the operations further comprise:
 providing the transaction recommendation to the specified customer; and   receiving at least one of a notification that the specified customer has authorized the transaction or a notification that the specified customer has declined the transaction.   
     
     
         3 . The system of  claim 2 , wherein the transaction recommendation comprises at least one of a recommended transaction amount or an identity of an entity. 
     
     
         4 . The system of  claim 1 , wherein the entity comprises a charitable organization. 
     
     
         5 . The system of  claim 1 , wherein the identified characteristic comprises at least one of a financial attribute, a geographic attribute, a demographic attribute, transaction history, or purchasing behavior. 
     
     
         6 . The system of  claim 1 , wherein the transaction model comprises information associated with at least one of a financial attribute of the customer group, a geographic attribute of the customer group, a demographic attribute of the customer group, transaction history of the customer group, or purchasing behaviors of the customer group. 
     
     
         7 . The system of  claim 4 , wherein the operations further comprise:
 receiving charitable organization information from a database, the charitable organization information comprising charity spending information; and   determining that the charitable organization spends less than a threshold percentage of its donations on operational costs.   
     
     
         8 . The system of  claim 1 , wherein the operations further comprise:
 receiving, from a third-party database, rating information for the entity; and   ranking the potential transactions based on the rating information.   
     
     
         9 . The system of  claim 2 , wherein the operations further comprise:
 generating a graphical user interface configured to receive a dollar amount input by the user.   
     
     
         10 . A computer-implemented method for recommending transactions to customers based on customer characteristics, comprising:
 receiving a request for a transaction recommendation associated with a specific customer via a computer network;   receiving a plurality of traits associated with the customer
 wherein receiving the plurality of traits comprises: 
 accessing, via an application programming interface, social network data associated with the customer, 
 identifying, based on the social network data, one or more elements in content accessed by the customer; and 
 determining one or more interests of the user based on the one or more elements, wherein the one or more interests are associated with the plurality of traits; 
   identifying, via one or more processors, a characteristic associated with a customer group based on the traits;   generating, by a machine learning process trained on customer data via the one or more processors, a transaction model associated with the identified characteristic, the transaction model identifying potential transaction information associated with an entity by the customer group;   determining a plurality of potential transactions using the transaction model, each potential transaction being associated with a likelihood of the customer completing the potential transaction;   ranking the potential transactions using the transaction model; and   generating a transaction recommendation for the specified customer based on the transaction model, the transaction recommendation comprising a transaction amount and a transaction recipient to receive the transaction amount from the customer.   
     
     
         11 . The method of  claim 10 , further comprising:
 providing the transaction recommendation to the specified customer, wherein the transaction information comprises a transaction amount.   
     
     
         12 . The method of  claim 11 , further comprising:
 receiving, via a client device, feedback from the specified customer indicating a relevance of the transaction recommendation to the specified customer; and   storing the feedback in a database.   
     
     
         13 . The method of  claim 12 , further comprising:
 training the transaction model based on received feedback from the customer group.   
     
     
         14 . The method of  claim 11 , further comprising:
 determining, based on the transaction model, a period of time for providing the transaction recommendation to the spccificd customer.   
     
     
         15 . The method of  claim 14 , wherein the period of time comprises a seasonal period associated with a national holiday. 
     
     
         16 . The method of  claim 14 , wherein the period of time comprises a period of time associated with a life event of the customer. 
     
     
         17 . The method of  claim 11 , wherein the transaction recommendation comprises an amount based on the plurality of customer traits associated with the customer. 
     
     
         18 . The method of  claim 10 , further comprising:
 providing, via a graphical user interface, a predetermined number of the ranked potential transactions, wherein each displayed transaction is selectable by the user.   
     
     
         19 . The method of  claim 10 , further comprising:
 generating a graphical user interface configured to receive a custom transaction amount input by a user.   
     
     
         20 . A non-transitory computer-readable medium storing instructions that, when executed by at least one processor, cause the at least one processor to perform operations comprising:
 receiving a request for a transaction recommendation associated with a customer via a computer network;
 receiving a plurality of traits associated with the customer wherein receiving the plurality of traits comprises:
 accessing, via an application programming interface, social network data associated with the customer, 
 identifying, based on the social network data, one or more elements in content accessed by the customer; and 
 determining one or more interests of the user based on the one or more elements, wherein the one or more interests are associated with the plurality of traits; 
 
   identifying, via one or more processors, a characteristic associated with a customer group based on the plurality of traits;   generating, by a machine learning process trained on customer data via the one or more processors, a transaction model associated with the identified characteristic, the transaction model identifying potential transaction information associated with an entity by the customer group;   determining a plurality of potential transactions using the transaction model, each potential transaction being associated with a likelihood of the customer completing the potential transaction;   ranking the potential transactions using the transaction model; and   generating at least one transaction recommendation for the customer based on the transaction model, the at least one transaction recommendation comprising a transaction amount and a transaction recipient to receive the transaction amount from the customer.